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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >M-ary sequential hypothesis tests for automatic target recognition
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M-ary sequential hypothesis tests for automatic target recognition

机译：用于自动目标识别的Mary顺序假设检验

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摘要

Several forms of sequential hypothesis testing algorithms are described and their performance as classification algorithms for automatic target recognition is evaluated and compared. Several forms of parameteric algorithms, as well as a sequential form of a useful nonparametric algorithm are considered. The primary focus is the design of algorithms for automatic target recognition that produce maximally reliable decisions while requiring, on the average, a minimum number of backscatter measurements. The tradeoffs between the average number of required measurements and the error performance of the resulting algorithms are compared by means of Monte-Carlo simulation studies.
机译：描述了几种形式的顺序假设检验算法，并对它们作为自动目标识别的分类算法的性能进行了评估和比较。考虑了几种形式的参数算法以及有用的非参数算法的顺序形式。主要重点是用于自动目标识别的算法设计，该算法可产生最大程度的可靠决策，同时平均需要最少数量的反向散射测量。通过蒙特卡洛模拟研究比较了所需测量的平均次数和所得算法的错误性能之间的权衡。

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